tag: machine learning

Designing Ultra Low Power AI Processors
By Ann Mutschler - 09 Apr, 2020 - Comments: 0

AI chip design is beginning to shift direction as more computing moves to the edge, adding a level of sophistication and functionality that typically was relegated to the cloud, but in a power envelope compatible with a battery. These changes leverage many existing tools, techniques and best practices for chip design. But they also are beginning to incorporate a variety of new approaches tha... » read more

What Is DRAM’s Future?
By Bryon Moyer - 09 Apr, 2020 - Comments: 0

Memory — and DRAM in particular — has moved into the spotlight as it finds itself in the critical path to greater system performance. This isn't the first time DRAM has been the center of attention involving performance. The problem is that not everything progresses at the same rate, creating serial bottlenecks in everything from processor performance to transistor design, and even the t... » read more

AI Requires Tailored DRAM Solutions
By Rambus - 08 Apr, 2020 - Comments: 0

For over 30 years, DRAM has continuously adapted to the needs of each new wave of hardware spanning PCs, game consoles, mobile phones and cloud servers. Each generation of hardware required DRAM to hit new benchmarks in bandwidth, latency, power or capacity. Looking ahead, the 2020s will be the decade of artificial intelligence/machine learning (AI/ML) touching every industry and applicatio... » read more

New Ways To Optimize Machine Learning
By Bryon Moyer - 02 Apr, 2020 - Comments: 1

As more designers employ machine learning (ML) in their systems, they’re moving from simply getting the application to work to optimizing the power and performance of their implementations. Some techniques are available today. Others will take time to percolate through the design flow and tools before they become readily available to mainstream designers. Any new technology follows a basic... » read more

More Multiply-Accumulate Operations Everywhere
By Ed Sperling - 02 Apr, 2020 - Comments: 1

Geoff Tate, CEO of Flex Logix, sat down with Semiconductor Engineering to talk about how to build programmable edge inferencing chips, embedded FPGAs, where the markets are developing for both, and how the picture will change over the next few years. SE: What do you have to think about when you're designing a programmable inferencing chip? Tate: With a traditional FPGA architecture you ha... » read more

How And Where ML Is Being Used In IC Manufacturing
By Mark LaPedus - 01 Apr, 2020 - Comments: 0

Semiconductor Engineering sat down to discuss the issues and challenges with machine learning in semiconductor manufacturing with Kurt Ronse, director of the advanced lithography program at Imec; Yudong Hao, senior director of marketing at Onto Innovation; Romain Roux, data scientist at Mycronic; and Aki Fujimura, chief executive of D2S. What follows are excerpts of that conversation. Part one ... » read more

What Machine Learning Can Do In Fabs
By Mark LaPedus - 25 Mar, 2020 - Comments: 0

Semiconductor Engineering sat down to discuss the issues and challenges with machine learning in semiconductor manufacturing with Kurt Ronse, director of the advanced lithography program at Imec; Yudong Hao, senior director of marketing at Onto Innovation; Romain Roux, data scientist at Mycronic; and Aki Fujimura, chief executive of D2S. What follows are excerpts of that conversation. L-R:... » read more

Memory Issues For AI Edge Chips
By Mark LaPedus - 23 Mar, 2020 - Comments: 3

Several companies are developing or ramping up AI chips for systems on the network edge, but vendors face a variety of challenges around process nodes and memory choices that can vary greatly from one application to the next. The network edge involves a class of products ranging from cars and drones to security cameras, smart speakers and even enterprise servers. All of these applications in... » read more

Week In Review: Auto, Security, Pervasive Computing
By Susan Rambo - 20 Mar, 2020 - Comments: 0

National Instruments is offering free online training courses to anyone anywhere, until the end of April to help support the engineering community during COVID-19 crisis. Some instructor-led virtual training is available at reduced cost. NIWeek has been postponed this year until August 3-5, 2020. Click here for more news about how the semiconductor industry is handling COVID-19. AI, machi... » read more

HBM2E Memory: A Perfect Fit For AI/ML Training
By Frank Ferro - 12 Mar, 2020 - Comments: 0

Artificial Intelligence/Machine Learning (AI/ML) growth proceeds at a lightning pace. In the past eight years, AI training capabilities have jumped by a factor of 300,000 (10X annually), driving rapid improvements in every aspect of computing hardware and software. Memory bandwidth is one such critical area of focus enabling the continued growth of AI. Introduced in 2013, High Bandwidth Memo... » read more

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